Phosphorylation-dependent control of Activity-regulated cytoskeleton-associated protein (Arc) protein by Tnik
Bibliographic record
Abstract
The remarkable capacity of neurons to reorganize their structure, function, and connections in an activity-dependent manner is supported by an extensive network of molecules and effectors. Among those, the 'hub' protein Activity-regulated cytoskeleton-associated protein (Arc, also known as Arg3.1) can be considered one of the central, as well as most versatile, players. Notably, Arc has been shown to maintain direct interactions with key synaptic factors like PSD95, TARPγ2, and CaMKII, as well as participate in many aspects of neuroplasticity such as trafficking of AMPARs and modeling of dendritic spines. How a single protein like Arc can do all this remains difficult to explain, but a complete answer to that question will certainly include a mix of protein post-translational modifications acting to confer molecular and functional specificity. Recently, sequence analysis of Arc protein led us to recognize two candidate phosphorylation sites specific to TRAF2 and NCK-interacting protein kinase (TNIK)--a member of the Germinal Center Kinases (GCK) subfamily that is considered a possible risk factor to different psychiatric disorders, including schizophrenia and bipolar disorder. Here, we present extensive biochemical, proteomics, and electron microscopy evidence supporting the influence of TNIK on Arc's subcellular distribution and oligomerization. Together, our findings position Arc as a substrate of TNIK and offer exciting new scenarios implicating these two factors in the context of the pathophysiology and potential treatment of neuropsychiatric disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".